Enterprises and government agencies increasingly rely on automated or predictive dialing systems for initiating communications with individuals. In particular, such systems can be used to automatically initiate outbound telephone calls. If a live person answering the telephone call is detected, a voice communication link is established between an agent associated with the enterprise or agency and the called party. If a voice mail system or answering machine is detected at the dialed number, the call may be terminated, or a prerecorded message left on the voice mail or answering machine. In order to increase the accuracy and efficiency of such systems, it is desirable to detect network intercept messages, such as operator intercept messages, which may include, for example, a notification that the dialed number has been disconnected or changed.
Telephone communication systems have relied on special tones to pass signals between interconnected pieces of equipment. For example, network intercept messages have typically been prefaced with a standardized special information tone (SIT) sequence notifying a calling piece of equipment that a telephone company or network intercept message follows. Accordingly, the SIT sequence allows network intercept messages to be distinguished from a private customer's voice mail answering machine. Communication systems for initiating telephone communications, such as automated or predictive dialing systems, can utilize SIT tones to classify the results of an outbound telephone call. In particular, such systems can mark a called number that resulted in the receipt of a special information tone for further investigation to determine, for example, the particular operator intercept message associated with the SIT sequence. Such messages may include notifications that the called number has been disconnected or changed. In addition, if an SIT sequence is not received, the communication system can classify the results of an outbound telephone call that results in the receipt of an automated voice (i.e. a non “hello” voice) as a private answering machine. A later attempt at reaching a live person at the dialed number can then be made.
Increasingly, and in particular with the increasing number of independent companies providing wireline and wireless telephony services, standardized SIT sequences are not provided as a preface to operator intercept messages. This reduces the accuracy and efficiency of outbound dialing systems. In addition, products are now available to consumers that mimic SIT sequences in an attempt to thwart attempts by solicitors and collection agencies to contact consumers. Accordingly, the ability of automated dialing systems to rely on the existence or veracity of SIT sequences to classify calls has been severely limited. At the same time, the need to accurately classify outbound calls has increased. In particular, consumer protection laws increasingly require that enterprises attempting to contact individual consumers obey consumers' instructions regarding how they can be contacted. In addition, failing to properly recognize a disconnected or changed number can result in wasted resources, and can result in a missed opportunity to update calling records.
Proposed solutions for classifying outbound calls without relying on the receipt of an SIT sequence include using automated speech recognition (ASR) and intelligent natural language processing (NLP) to recognize, parse and automatically respond to network messages. In an ASR based system, a message is parsed to determine what words have been spoken. An appropriate response may then be taken, provided that the spoken words are accurately recognized and the words match a preprogramed sequence. In an approach utilizing NLP, the spoken words are further analyzed to determine their meaning. If that meaning is accurately discerned, the call can be accurately classified. However, both ASR and NLP based systems require significant processing power, and have been considered unreliable. Additionally, a solution must be developed for each language in which the ASR or NLP system is implemented, and the processing requirements may be too intensive for deployment in connection with existing automated dialing systems or for cost effective deployment in newly developed systems.